MCET NETWORK

In general, the work continued what was started in the ODPP project, extending the simulated scenarios, particularly those related to Demand Side Flexibility. Then, based on the consolidation of these scenarios and with the goal of bringing the tool closer to stakeholders who might use it, a workshop was held in April. This workshop brought together members of regulatory bodies and academia, where Switch, its potential, and the results obtained by the Chilean MCET team were presented. Additionally, a discussion panel emphasized the relevance of these tools in decision-making.

In regard to the engagement with different stakeholders, contact was made with the Ministry of Energy of Chile to expose the capabilities of using the Switch model as an alternative tool to other models already in use. Additionally, a Discord Channel called ‘MCET Chile Modeling Hub’ was launched following the workshop. It currently has 16 members ranging from the regulator to the academia. Through this communication channel we have provided different spaces to ask questions and to access the official Switch material.

Beyond the work carried out with key actors in Chile, in the final phase of the MCET project, a three-stage collaboration with the Ministry of Energy and Mines (MEM) of Dominican Republic was initiated to introduce the capabilities of using the Switch model in exploring various scenarios for the future development of the power system, reflecting potential pathways for the Dominican Republic's energy transition and the evolution of its power system for the 2024-2050 horizon, as well as alternatives for the use of the ETA program as a financing mechanism.

The team members who participated in this project were Matías Negrete-Pincetic, Nicolás Lobos, Manuel Portilla and María José Galilea.

Power system in 2050, modeling a system with near-zero emissions to conduct a prescriptive analysis based on various technological developments. Eleven scenarios were developed:

• Reference: Includes candidate projects for Solar, Wind, Gas with CCS, Geothermal, Biomass, BESS, CSP-TES, PHS, CAES, and Hydrogen Storage.

• Only Renewables with Storage: Same as the reference scenario but without Gas with CCS and Hydrogen Storage.

• Only Renewables with Storage and Hydrogen: Same as the previous scenario, but includes Hydrogen-based storage.

• Restricted Transmission Expansion: Four scenarios where transmission expansion is limited to 75%, 50%, 25%, and 0% of the reference capacity.

• Reference with Zonal Flexible Loads: Same as the reference, but with flexible loads that can shift between nodes in one zone.

• Reference with Non-Zonal Flexible Loads: Same as the zonal flexible loads scenario, but loads cannot shift between nodes.

• Renewables with Zonal Flexible Loads: Same as the renewables-only scenario, but with flexible loads that can shift between nodes in one zone.

• Renewables with Non-Zonal Flexible Loads: Same as the previous scenario, but   loads cannot shift between nodes.

Broadly speaking, at the level of results, in the Reference scenario, complementary behavior is observed in energy dispatch, particularly Solar PV during the day and at night, Gas CCS, CSP-TES and BESS are mainly used as peak generation. In addition, biomass and geothermal act as base generation, but with seasonal deviations during the day due to the change in the availability of certain technologies.

When observing the transmission requirement, greater investments in Tx are concentrated in lines from the south to the center to export wind energy from the area and the rest of the expansions are focused on strengthening the northern lines to export more solar energy and CSP-TES. For the scenario with only renewables with storage, a considerable increase in the capacity requirement is observed, increasing by 75.47% compared to the requirement in the Reference scenario. In this case, storage in a predominantly variable scenario plays a fundamental role in its different forms and duration, particularly observed in the hours where solar generation does not participate, BESS and PHS storage contribute with the required

energy.

One key result worth noting is regarding marginal costs in scenarios comparing renewable-only participation (REN) versus a reference scenario (Ref). In the renewable-only scenario, the marginal costs are nearly zero for the majority of the time, which contrasts with the reference scenario, which shows significant fluctuations in marginal costs.

The consistent low marginal costs in the renewable-only scenario suggest that a high penetration of renewable energy sources could lead to periods where the cost of generating additional electricity is minimal. This outcome challenges traditional market operations and compensation mechanisms for energy production, as the usual price signals for generating electricity are significantly diminished. The slide underscores the need to rethink energy market structures and remuneration strategies to accommodate the economic realities of a predominantly renewable energy system. This rethinking is essential to ensure the sustainability and efficiency of the energy market in the face of increasing renewable energy integration.

When we observe the four scenarios with restricted expansion of the transmission one of the main elements that can be analyzed is the areas with a critical need for transmission infrastructure. In the case of the modeled scenarios, two phenomena are observed. In the first place, with a strong constraint (meaning a smaller amount of Tx capacity to expand), the investment is prioritized in expanding the Kimal - Alto Jahuel line, which connects the north of the country with the center, i.e. the solar resource with the main consuming zone. On the other side, when we have a more relaxed level of restriction, the expansion in the central and southern area is prioritized, connecting the wind resource with the main consuming zone. It is also important to mention that the total restriction of Tx expansion increases total systemic costs by more than 7%, compared to the Reference scenario.

Regarding the impact of Demand Side Flexibility on the power system of 2050, in terms of transmission needs, we see a similar effect in both scenarios (Reference and REN) when we allow demand side participation, with a decrease in investment, whose effect is even greater when zonal DSF is available, reaching more than 30% less. For the generation mix, this one is transformed in order to exploit the synergies with particular technologies, such as photovoltaic solar energy, worth noting the decreased need for technologies that provide flexibility, such as Gas CCS, CSP-TES and storage technologies (BESS, Hydrogen, PHS and CAES) in the Reference scenario.

Now regarding the dispatch of the generation resources and the shift of the consumed energy, as expected, load is mainly shifted outside the hours when there is less availability of lower-cost energy. When considering the option of shifting load zonally (in this case, SEN), it is possible to highlight the value of planning not only the generation and transmisión infrastructure but also the controlled growth of demand. Moreover, when load shifting occurs, it primarily targets periods outside of those with limited availability of lower-cost energy. In considering the option of zonal load shifting within the SEN framework, the importance of comprehensive planning becomes evident. This planning should encompass not only the infrastructure for generation and transmission but also strategies for the controlled growth of demand. This holistic approach ensures an optimized energy system that can meet future needs efficiently and sustainably.

Collaboration Overview

The collaboration between the Chilean team and the government of the Dominican Republic was born with the objective of complying with adaptation and extending open electricity planning models to meet the needs of stakeholders, in April, 2024. This collaboration was motivated by the ETA carbon finance platform where the country is analyzing the alternatives to finance the carbon mitigation measures using the funds obtained with this initiative. The idea of this collaboration was to deliver a more detailed version of a planning process for the electricity sector in the Dominican Republic based on the data source available and provided.

In particular, this collaboration was divided into three stages. The first stage of this

collaboration aimed to prepare an unofficial update of the estimate of the National

Greenhouse Gas Inventory for the years 2019-2023 for the electricity production sector. The second stage consisted of developing a simulation of the power system's operation using Switch for the years 2021 and 2023 to approximate the emissions and the intensity factor of the Dominican power system. The last stage of the collaboration consisted of defining different scenarios/futures built from the estimates and objectives that RD may have regarding the electrical system and the planned energy transition, to provide a tool to analyze their participation on ETA.

Emissions Inventory

The initial estimate of CO2 emissions from electricity generation was based on annual generation data from the RD ISO's "Annual Report of Economic Transactions" and calculated using the 2006 IPCC Guidelines. Emissions were estimated by multiplying fuel consumption by emission factors, with the Tier 1 Method applied for simplicity. Fuel consumption was estimated from energy generation data and the corresponding heat rates, then converted to emissions using default factors. This preliminary estimate, calibrated with detailed input from

the DR team, provides a basis for comparison with results from Switch simulations for 2021 and 2023, serving as a starting point for further analysis.

2021 and 2023 Calibration

The model is based on data from the 2018 "Study of Acceptable Penetration of Renewable Energy in the Dominican Republic," developed by the University of Chile's Energy Center for the IDB and the Dominican Republic's Superintendence of Electricity. Using information from various Dominican energy agencies, the transmission network and operational parameters of thermal power plants for 2021 were established. The model underwent calibration with updated data on generation parameters, costs, capacity factors, and demand profiles, based on real information provided by the DR team. The final version simulates the SENI's operation for both 2021 and 2023 with 8760 hourly precisions, using real demand and renewable resource data. Results are summarized in figures and paragraphs for each year.

In 2021, the Dominican Republic's annual electricity consumption was 18,887.33 GWh, with generation from the Switch model estimated at 19,386.08 GWh and emissions totaling 13,108.4 Gg CO2, resulting in an emission intensity of 676.18 kgCO2/MWh. System losses were 1.82%, closely matching real-world data. Wind, hydro, and solar energy saw slight increases in participation, while fossil fuel contributions varied, highlighting the importance of accurate data inputs in modeling. In 2023, demand rose to 20,958.63 GWh, with generation reaching 21,473.92 GWh, emissions of 14,499.4 Gg CO2, and an emission intensity of 675.21 kgCO2/MWh. Renewable energy participation increased slightly, with wind and solar both growing, while natural gas and coal showed varying shifts in contribution. System losses were slightly higher at 2.46%. These variations underscore the importance of accurate data inputs and calibration in modeling. Nevertheless, it is important to mention that there will always be gaps between the model results and the real-time operation of the power system, so this provides a fair approximation to how the power system operated. 

2024-2050 Planning

The long-term projection was simulated from the year 2024, based on the 2023 calibration mentioned earlier. This calibration primarily uses demand profiles, renewable energy profiles, the existing transmission structure, operational parameters, non-fuel costs of the power plants, and observed fuel costs for that year. From this, scenarios are defined based on how the 2023 data is projected. These projections include different evolutions of investment costs, fuel prices, demand growth, interest and discount rates, candidate technologies, and zones where they could be installed. The goal is to project how emissions might evolve in each scenario and thus quantify the credits obtained using the ETA methodology.

Specifically, the time horizon considers one-year investment periods from 2024 to 2050, with each year consisting of 6 representative 24-hour days. The existing generation fleet as of 2023 is considered, along with renewable, natural gas, and storage projects included in the energy planning documents provided. The analysis considered four development scenarios, differentiated by the potential capacity for wind and solar generation development, as well as their possible adoption rates. The simulated scenarios are described below:

• Base Free Scenario: Between 2024 and 2030, it considers the addition of projects identified with a definitive concession and in construction. For the period between 2030 and 2050, renewable capacity growth is restricted based on the potential identified in previous stages, and investments in new gas-fired thermal units are allowed.

• Base Free CN Scenario: Assumes an upper emissions limit that progressively decreases between 2033 and 2050, aiming to reduce emissions after their peak in 2033, with the goal of achieving carbon neutrality by 2050.

• Base Restricted Scenario: Unlike the Base Free scenario, from 2030 to 2040, investments are allowed only in additional capacity associated with projects that currently have a definitive concession but are not under construction. From 2040 to 2050, investments are allowed in additional capacity from projects with provisional concessions. Additionally, investments in new gas thermal units with 97% CCS are permitted.

• Base Restricted CN Scenario: Unlike the Base Restricted scenario, this assumes an upper emissions limit that progressively decreases between 2040 and 2050, aiming to reduce emissions after their peak in 2040, with the goal of achieving carbon neutrality by 2050.

The information used to define these scenarios was supplemented with international references, such as NREL's Electricity Annual Technology Baseline and the EIA's World Energy Outlook, particularly for cost projections.

At a general level, the results show that in the Base Free Scenario, there is a significant investment in renewable energy technologies such as solar, wind, and energy storage, leading to a more cost-efficient expansion of the system. However, in restricted scenarios, the additional limitations on renewable adoption result in higher total costs and delays in reaching peak emissions, challenging short- and medium-term emission reduction targets. Gas generation plays a key role in the energy mix, and without the progressive adoption of renewable sources, emissions could peak around 2040 or later, highlighting the importance of carbon capture technologies for the energy transition and also the relevance of promoting the implementation of non-conventional renewable energies through the reduction of entry barriers that could delay their entry.

The analysis shows that in restricted scenarios, the peak of emissions is reached in 2040, posing a challenge to meeting the emissions intensity reduction targets outlined by the ETA framework. Only the unrestricted scenarios generated carbon credits by 2050, and only the Base Free CN Scenario did so in a relevant amount. The possible income from credits was evaluated in relation to the additional investment needed to go from the Base Restricted scenarios to the Free counterparts (with or without CN). It was noted that the Base Free CN Scenario generated enough credits to cover from a 5.3% to a 13.2% of the additional renewable generation needed. This range was obtained considering different possible prices (US$20/ton to US$50/ton) for the carbon credits generated through the ETA program. In any case it was clear that the main investment would have to take place in an accelerated manner in order for the Dominican Republic to be able to make any relevant amount of credits before 2050.

While the exercise revealed the application of Switch for a potential carbon market participation it also made visible the complexities that a Dominican Republic would face. Since the ETA mechanism is based on countries determining an ambitious emission reduction curve to consider as a standard, the solutions achieved with Switch can provide insight as to this determination. This tool allows the country to consider different generation mixes they would need to have in order to achieve emissions reductions, and the time frame in which the investment would have to take place, being therefore a tool for the country to negotiate its participation in a carbon market. It is also worth noting that these are still emerging markets, where the potential carbon prices are not clear, and will depend on the total amount of credits generated.

Finally, the work carried out demonstrates the potential of using the Switch model in the evaluation of electricity system development alternatives for the energy transition. In particular, the tool was used in the evaluation of various future development scenarios for the Dominican Republic, reflecting potential pathways for its energy transition as well as alternatives for the use of the ETA program as a financing mechanism. As part of the potential future work, in terms of the modeling exercise, the internalization of barriers for the integration of variable renewable generation sources and storage systems, as a result of market rules, public policies, financing conditions, etc., could be considered. Additionally, to the transfer of competencies for the use of the Switch model independently by the technical teams of the Dominican Republic.